As the general population is living longer, most medical costs associated with the aging population are increasing. The costs associated with serious and chronic diseases, such as cancer, are growing in an unsustainable manner. For example, cancer costs are projected to be the highest growth area in healthcare spending without a commensurate improvement in outcomes. Approximately $125 billion was spent in 2010 on cancer care in the United States alone, and estimates are that approximately 15-30% of the spending can be categorized as a consequence of unnecessary or inappropriate care, where too little or too much care for an individual patient leads to less than optimal clinical outcomes and excessive expenses (hereinafter “Adverse Variance”).
Under the current system, for every 100 people with a serious medical condition receiving care, there is on average a 20% rate of Adverse Variance, meaning that too little or too much care was delivered to an individual patient. Thus, a less than optimal clinical outcome occurs in 20% of the patients receiving care, resulting in an increase in total cost of care at the population level 100% of the time.
Conventional techniques to control costs, such as clinical pathways and disease management, are typically ineffective, and there are no quality alternatives that currently exist in the market today.
The current prior authorization infrastructure that enables a payer to determine that a medical service is a covered benefit under a patient's health plan is expensive and takes too much time, which can adversely affect clinical outcome by delaying necessary care.
As advancements in technology and medicine continue to occur, the science and clinical practice of caring for diseases (such as cancer, cardiovascular disease, pulmonary disease and behavioral health) are rapidly evolving. Often, medical professionals (e.g., oncologists) have a difficult time keeping up with these advancements. These advancements, such as next generation genetic sequencing, are typically complex and may present major issues for health plans and medical professionals. As a result, health plans will likely need more tools and support to manage their medical (e.g., oncology) business. Similarly, medical professionals (e.g., physicians) will need more decision support tools to practice best medicine and stay in business.
A clinical outcome tracking and analysis (COTA) module is a tool to, for example, enable medical professionals and/or other users to practice better medicine, better manage and locate specific information associated with a disease and/or patient, and facilitate improved control of cost.
The parameters of clinical outcome tracking and analysis include sorting, outcome tracking, Eastern Cooperative Oncology Group (ECOG) performance status; toxicity to therapy and cost of care. In one aspect, a method and system include the COTA module that receives, from a client device operated by a user, one or more parameters to sort a plurality of data records, and, in response to the receiving, sorts the data records based on the received parameters. A nodal address, indicating one or more variables, is applied to the sorted set of patient medical records to determine a clinically relevant set of patient medical records as the sorted set of patient medical records satisfying the one or more variables. The COTA module then analyzes the clinically relevant set of patient medical records and communicates at least a portion of the classified and sorted data records and the updated data records to a client device for display.
Each data record includes data associated with a disease and data associated with patients currently having the disease or patients who previously had the disease. The COTA module can receive the data from an electronic medical record (EMR), from a user, from a medical professional, from an expert, or from any other source.
The COTA module can enable the user to perform various analyses on one or more of the data records. For example, the COTA module can enable a comparison of data or of tracked outcomes between patients can identify a specific patient as a candidate for a specific treatment or drug, can communicate an analysis tool to the client device to facilitate analysis of, for instance, the classified and sorted data records or to enable comparison of Kaplan Meier curves, and can determine, based on the tracking, whether a specific doctor associated with a patient is treating the patient in accordance with treatment techniques of other doctors treating other (similar) patients.
The COTA module may also transmit an alert to the client device upon the occurrence of a trigger. A trigger may be, for example, at diagnosis, at progression, at dose change, at drug change, at toxicity, when trending towards variance from a desired outcome, and/or at a specific time.
The COTA module tracks consequences of treatment choices and reports on outcomes associated with the use of COTA Nodal Addresses (CNAs). It accounts for biological variance upfront by grouping patients in a patient population, which effectively removes biological variance as a factor in value of care, leaving treatment variance as a predominant factor in treatment outcome. The COTA module receives, collects, and records personal health information from each patient in the patient population in a database, and sorts the personal health information. Like personal health information is classified, and types of patients in the patient population are grouped based on the personal health information by generating and assigning a plurality of nodal addresses within the COTA module. Each CNA is represented as a discrete punctuated string of digits comprising a prefix, a middle, and a suffix that represent a set of preselected variables that partition the sorted and classified information into a clinically relevant set of health information. A plurality of CNAs reduces trillions of possible permutations to a reduced number of clinically meaningful permutations based on the discrete punctuated string of digits representing each nodal address that enable analysis of first behavioral and then consequent clinical and cost outcome variance from an ideal value, expressed as best clinical outcome at lowest possible cost, in a requisite time needed to alert for necessary care and avoidance of unnecessary care, thereby increasing the value of care, meaning better clinical outcomes at a lowest possible cost; reduce processing requirements and time for processing to make real-time monitoring of medical provider performance efficient based on the discrete punctuated string of digits representing each nodal address and based on the reduction in permutations; and enable prediction of key points in time at which behavioral variance is likely to occur and interrupting treatment flow to avoid over-/under-utilization of care to prevent the behavioral variance.
The described invention provides CNA-guided care. CNA-guided care has two faces, which together, through the triad of a health care provider, a payer, and the patient suffering from a disease, enables value based care delivery in the United States through the application of CNAs.
The first face, the enabling tool, comprises interactions between a medical care provider, a computer containing a processor comprising a first COTA module, a first client device comprising a second COTA module that is communicatively linked to the first COTA via a network, and a payer. It enables a payer to transmit via the first client device comprising a second COTA module communicatively linked to the first COTA module of the processor, a communication over the network to the processor identifying a health care service under consideration for a patient whose health plan benefits cover the service; indicating that the service is for the purpose of diagnosing or treating a medical condition; and identifying variables selected by the payer. Upon receiving this communication from the payer, the first COTA module can transmit to the second COTA module information comprising (i) the clinical outcome data for each CNA, (ii) the adverse variance data for each medical provider at each CNA including both necessary care that is absent and unnecessary care contributing to the medical care provider's adverse variance for patients at each nodal address at key points in time during treatment; (iii) a cost report comprising cost data in real time for treating each patient in the patient population assigned to the CNA; and (iv) graphic analyses correlating one or more of (1) cost of care to clinical outcome; (2) incidence and severity of toxicity to cost of care and clinical outcome of care; and (3) therapy and quality of life. Based on this information, when the payer can establish at key points in time, (a) that the medical service is an appropriate delivery or level of service, considering potential benefits and harms to the patient; (b) that the medical service is effective in improving health outcome by improving clinical outcomes and reducing total cost of care; that the service is cost-effective for the medical condition being treated and the clinical outcome, compared to alternative health interventions or no intervention; and that the service follows generally accepted medical practice, the payer can approve payment to the medical care provider for the medical service for the patient.
From the payer's vantage point, this enabling tool can be effective to eliminate precertification for testing, diagnostics, and therapeutic choices; eliminate prior authorization; and eliminate the need for referrals. From the medical care provider's vantage point, it reduces the time necessary to pay the provider for healthcare. Accordingly, the enabling tool enables healthcare to optimize fee for service based reimbursement and to move from fee for services to risk-based care reimbursement (for example by bundling services),
The second face of CNA-guided healthcare comprises interactions between the computer containing the processor comprising the first COTA module, a second client device comprising a third COTA module that is communicatively linked to the first COTA module via a network, and the patient. Through a series of communications between the first COTA module and the patient, CNA-guided healthcare, first, provides the patient with information sufficient for the patient to get a complete medical evaluation of his/her condition and for the first COTA module to assign a CNA to the patient; second, using the CNA, it shows the patient treatment options based on geography, clinical outcome, cost and other patient-set criteria that enable the patient to select care optimized to avoid adverse variance; third it shows the patient health care providers in his/her area who follow CNA guided care that have the best outcomes at an acceptable cost of care.